Human observation is currently employed to capture field data on the behavior of shoppers. Human observation has disadvantages, including subjectivity, limitations on sample size inherent in the number of shoppers a single observer can monitor, distractions, and high cost. Another tool is video analysis, which includes video surveillance (instead of in person human observation) and automated surveillance cameras. Eye tracking, whereby the shopper is provided with a pair of glasses, is another mechanism that can be used. There are also cell phone related techniques, e.g., measuring smart phone Wi-Fi or cell phone signals, facial recognition algorithms, and RFID solutions which require that every product in the store is tagged with an RFID tag. See, e.g., U.S. Pat. No. 8,219,438 B1 to Moon et al. for Method and System for Measuring Shopper Response to Products Based on Behavior and Facial Expression issued on Jul. 10, 2012; US 2011/0293137A1 to Guruman et al. for Analysis of Three-Dimensional Scenes, published Dec. 1, 2011; U.S. Pat. No. 8,150,142 B2 to Freedman, for Depth Mapping Using Projected Patterns issued Apr. 3, 2012; and US 2010/0007717A1 to Spektor et al. for Integrated Processor for 3D Mapping, published Jan. 14, 2010. U.S. Pat. No. 6,711,293, issued to Lowe on Mar. 23, 2004, entitled Method And Apparatus For Identifying Scale Invariant Features In An Image And Use Of Same For Locating An Object In An Image discloses digitally recording visual characteristics of, e.g., a person, in order to facilitate identifying a returning person with the same ID. well known 3D scanners applicable here are discussed in http://en.wikipedia.org/wiki/3D_scanner. The Microsoft “Kinect”™, suitable for use with the claimed subject matter is discussed in http://en.wikipedia.org/wiki/Kinect.